Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A fever epidemic detection method, used in a fever epidemic detection system for automatically and widely detecting fever epidemic in a region via Internet of Things (“IoT”), comprising: calculating a number of people passing through the region during a predetermined time interval; detecting temperature of the region in the predetermined time interval to obtain an environment average temperature and calculating an environment average temperature parameter according to the environment average temperature; using a thermal imager to measure temperature of each person in the region to obtain a measured temperature; calibrating the measured temperature with a calibration factor to calculate a calibrated temperature, wherein the calibration factor is with respect to a type of the thermal imager; determining whether the calibrated temperature is within a predetermined normal temperature range so as to generate a determination result; generating a first alerting message and outputting the first alerting message and a corresponding calibrated temperature if the determination result indicates that the calibrated temperature is not within the normal temperature range, and transmitting the first alerting message and the corresponding calibrated temperature to an external device; counting a number of the first alerting messages accumulated during the predetermined time interval and calculating a ratio of the number of the first alerting messages to the number of people passing through the region during the predetermined time interval generating a third alerting message once the ratio is larger than a predetermined ratio; and transmitting the third alerting message, the ratio, the corresponding number of the first alerting messages, and the number of people to the external device; wherein the third alerting message indicates that among people who have passed through the region during the predetermined time interval, the people whose temperatures are abnormal are equal to or more than a certain percentage of the people who have passed through the region.
A method for automatically detecting fever epidemics in a region using Internet of Things (IoT). It involves counting the number of people passing through a region during a specific time. The method also measures the region's temperature to get an environment average and a corresponding parameter. A thermal imager measures each person's temperature, which is then calibrated using a factor specific to the imager type. If a person's calibrated temperature is outside a normal range, a "first alert" message with their temperature is generated and sent to an external device. The method counts these "first alerts" over the specified time and calculates a ratio of these alerts to the total number of people. If this ratio exceeds a preset value, a "third alert" is generated and sent to the external device, indicating that a significant percentage of people in the region have abnormal temperatures, along with the ratio, alert count, and total people.
2. The fever epidemic detection method according to claim 1 , further comprising: calculating a group average temperature in every predetermined time interval according to the measured temperature, and calculating a group average temperature parameter according to the group average temperature; and adjusting the normal temperature range according to the environment average temperature parameter and the group average temperature parameter.
A method for automatically detecting fever epidemics in a region using Internet of Things (IoT). It involves counting the number of people passing through a region during a specific time. The method also measures the region's temperature to get an environment average and a corresponding parameter. A thermal imager measures each person's temperature, which is then calibrated using a factor specific to the imager type. If a person's calibrated temperature is outside a normal range, a "first alert" message with their temperature is generated and sent to an external device. The method counts these "first alerts" over the specified time and calculates a ratio of these alerts to the total number of people. If this ratio exceeds a preset value, a "third alert" is generated and sent to the external device, indicating that a significant percentage of people in the region have abnormal temperatures, along with the ratio, alert count, and total people. Additionally, the method calculates a group average temperature and its parameter from the measured temperatures for each time interval, then dynamically adjusts the normal temperature range based on both the environment and group average temperature parameters.
3. The fever epidemic detection method according to claim 1 , further comprising: wherein a second alerting message is generated once the number of the first alerting messages is larger than a predetermined message number, and the second alerting message and the number of the first alerting messages are outputted.
A method for automatically detecting fever epidemics in a region using Internet of Things (IoT). It involves counting the number of people passing through a region during a specific time. The method also measures the region's temperature to get an environment average and a corresponding parameter. A thermal imager measures each person's temperature, which is then calibrated using a factor specific to the imager type. If a person's calibrated temperature is outside a normal range, a "first alert" message with their temperature is generated and sent to an external device. The method counts these "first alerts" over the specified time and calculates a ratio of these alerts to the total number of people. If this ratio exceeds a preset value, a "third alert" is generated and sent to the external device, indicating that a significant percentage of people in the region have abnormal temperatures, along with the ratio, alert count, and total people. Additionally, if the count of these "first alerting messages" surpasses a predetermined threshold, a "second alerting message" is generated and outputted, detailing this high alert count.
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July 28, 2020
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